Automated Error Determination Propagation via Priority Matrices
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Solution Overview
Problem
Current call home systems face challenges in prioritizing and propagating data packages efficiently across multiple devices to a central repository, leading to delays in transmitting urgent data due to limited connections and manual searching inefficiencies, which can result in missed critical information.
Innovation Solution
An automated system and method for propagating data priority determinations using modules such as unsent data package, local data package order, data package transmission, local priority matrix update, and connection modules to prioritize and update data packages, ensuring timely and accurate transmission of high-priority data across a network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual searching is used to find high priority data packages, then users can identify important information, but time is wasted and critical information may be missed
Solution Approach 1:
The system pre-calculates and assigns priority values to data packages before they need to be searched. Priority matrices are computed in advance based on device importance, data type, and other criteria, so when a search is needed, high priority packages are already identified and marked, eliminating the need for time-consuming manual sorting while ensuring accurate identification of critical information
Solution Approach 2:
The patent introduces an intermediary priority calculation system that acts between data generation and data retrieval. This intermediary layer automatically computes priority scores and tags data packages accordingly, serving as a mediator that prepares the data in advance so users don't need to manually search through unsorted data, thus reducing search time while maintaining accurate identification of high priority items
2Productivity
If call home devices prioritize their local data packages, then transmission efficiency improves, but system-wide priority cannot be calculated
Solution Approach 1:
The patent merges local priority matrices from multiple call home devices with central system information to create a unified system-wide priority view. The central server collects priority data from various sources, combines it with system-level context, and redistributes updated priority matrices to devices. This merging allows each device to maintain local prioritization for immediate transmission efficiency while also having access to system-wide priority calculations for broader context
Solution Approach 2:
The system implements a feedback loop where priority matrices are continuously updated and redistributed. Central servers receive data from call home devices, recalculate priorities based on system-wide conditions, and send updated priority matrices back to devices. This feedback mechanism enables devices to operate with current system-wide priority information, maintaining both transmission efficiency and accurate system-wide priority calculation
3Ease of operation
If microcode is loaded to provide system-wide priorities, then priority information becomes available, but the process is infrequent and lengthy
Solution Approach 1:
Instead of relying on infrequent microcode loading, the system implements periodic updates of priority matrices through automated communications between central servers and call home devices. Priority information is refreshed at regular intervals or triggered by specific events, ensuring devices have current system-wide priority data without requiring lengthy microcode loading processes. This periodic action maintains information availability while minimizing time loss
Solution Approach 2:
The patent uses copying of priority matrix data from central servers to local devices rather than loading complex microcode. The central server maintains a master priority database and copies relevant priority information to call home devices as needed. This copying approach provides system-wide priority information quickly and efficiently, avoiding the time-consuming microcode loading process while keeping devices synchronized with central priority decisions
Data Source
AI summary
An apparatus, system, and method are disclosed for automated data determination propagation. A data package source collects data and compiles the data into data packages. A local data package prioritization module determines a prioritized order of the data packages based on a local priority matrix. The local data package prioritization module sends the data packages in the prioritized order over a temporary data connection to a central data package prioritization module. The local data package prioritization module updates the local priority matrix over the temporary data connection based on a central priority matrix. The central data package prioritization module receives the data packages and makes one or more updates to the central priority matrix based on the data packages.